Mutation patterns and structural correlates in human immunodeficiency virus type 1 protease following different protease inhibitor treatments

Abstract

Although many human immunodeficiency virus type 1 (HIV-1)-infected persons are treated with multiple protease inhibitors in combination or in succession, mutation patterns of protease isolates from these persons have not been characterized. We collected and analyzed 2,244 subtype B HIV-1 isolates from 1,919 persons with different protease inhibitor experiences: 1,004 isolates from untreated persons, 637 isolates from persons who received one protease inhibitor, and 603 isolates from persons receiving two or more protease inhibitors. The median number of protease mutations per isolate increased from 4 in untreated persons to 12 in persons who had received four or more protease inhibitors. Mutations at 45 of the 99 amino acid positions in the protease-including 22 not previously associated with drug resistance-were significantly associated with protease inhibitor treatment. Mutations at 17 of the remaining 99 positions were polymorphic but not associated with drug treatment. Pairs and clusters of correlated (covarying) mutations were significantly more likely to occur in treated than in untreated persons: 115 versus 23 pairs and 30 versus 2 clusters, respectively. Of the 115 statistically significant pairs of covarying residues in the treated isolates, 59 were within 8 A of each other-many more than would be expected by chance. In summary, nearly one-half of HIV-1 protease positions are under selective drug pressure, including many residues not previously associated with drug resistance. Structural factors appear to be responsible for the high frequency of covariation among many of the protease residues. The presence of mutational clusters provides insight into the complex mutational patterns required for HIV-1 protease inhibitor resistance.

FIG. 1.

Histograms of mutation frequency according to the number of protease inhibitors (PIs) received. The median number of mutations (differences from the consensus B sequence) increased from 4 in untreated persons to 12 in persons receiving ≥4 inhibitors.

FIG. 2.

PCA of the 45 positions associated with protease inhibitor treatment. The graph is a two-dimensional projection of the distances among the 45 positions, where the similarity between any two positions is measured by their binary (phi) correlation coefficient among persons who have received at least one inhibitor. Positions with high degrees of comutation are close together, and positions with low or negative degrees of comutation are far apart. These relationships are modeled as consistently as possible within the framework of a two-dimensional plot.

FIG. 3.

The 50 most highly correlated residues in isolates from treated persons are shown superimposed on the locations of these residues within the folded enzyme. The blue lines represent positively correlated residues (n = 44; phi > 0.2); the red lines represent negatively correlated residues (n = 7; phi < −0.2). The diameter of each line is proportional to the correlation coefficient of the residue pair. The lines connect the beta carbons of each residue, with the exception of the glycines at positions 48 and 73, which are connected to other residues by their alpha carbons. Each correlated pair is shown twice, once in each monomer.

FIG. 4.

Six representative clusters from Table 4. Each position in a cluster demonstrates statistically significant mutational covariation with each of the other positions within a cluster. (A) Positions 10, 63, 71, 90, and 93; (B) positions 10, 46, 71, 90, and 93; (C) positions 10, 71, 73, 84, and 90; (D) positions 10, 46, 71, 84, and 90; (E) positions 10, 48, 54, and 82; (F) positions 10, 24, 46, 54, and 82. The clusters are only shown on one monomer of the protease dimer. The side chains of the residues within each cluster are shown on the protease backbone. Oxygen is shown in red, nitrogen in blue, carbon in gray, and sulfur in yellow.